The present invention relates to a monitoring system, or more in particular to an entering object detecting method and an entering object detecting system for automatically detecting persons who have entered the image pickup view field or vehicles moving in the image pickup view field from an image signal.
An image monitoring system using an image pickup device such as a camera has conventionally been widely used. In recent years, however, demand has arisen for an object tracking and monitoring apparatus for an image monitoring system by which objects such as persons or automobiles (vehicles) entering the monitoring view field are detected from an input image signal and predetermined information or alarm is produced automatically without any person viewing the image displayed on a monitor.
For realizing the object tracking and monitoring system described above, the input image obtained from an image pickup device is compared with a reference background image, i.e. an image not including an entering object to be detected thereby to detect a difference in intensity (or brightness) value for each pixel, and an area with a large intensity difference is detected as an entering object. This method is called a subtraction method and has found wide applications.
In this method, however, a reference background image not including an entering object to be detected is required, and in the case where the brightness (intensity value) of the input image changes due to the illuminance change in the monitoring view field, for example, the reference background image is required to be updated in accordance with the illuminance change.
Several methods are available for updating a reference background image. They include a method for producing a reference background using an average value of the intensity for each pixel of input images in a plurality of frames (called the averaging method), a method for sequentially producing a new reference background image from the weighted average of the present input image and the present reference background image, calculated under a predetermined weight (called the add-up method), a method in which the median value (central value) of temporal change of the intensity of a given pixel having an input image is determined as a background pixel intensity value of the pixel and this process is executed for all the pixels in a monitoring area (called the median method), and a method in which the reference background image is updated for pixels other than in the area entered by an object and detected by the subtraction method (called the dynamic area updating method).
In the averaging method, the add-up method and the median method, however, many frames are required for producing a reference background image, and a long time lag occurs before complete updating of the reference background image after an input image change, if any. In addition, an image storage memory of a large capacity is required for an object tracking and monitoring system. In the dynamic area updating method, on the other hand, a intensity mismatch occurs in the boundary between pixels with the reference background image updated and pixels with the reference background image not updated in the monitoring view field. Here, the mismatch refers to a phenomenon that it falsely looks as if a contour exists at a portion where the background image has in fact a smooth change in intensity due to generation of a stepwise intensity change at an interface between updated pixels and those not updated. For specifying the position where the mismatch has occurred, the past images of detected entering objects are required to be stored, so that an image storage memory of a large capacity is required for the object tracking and monitoring system.
An object of the present invention is to obviate the disadvantages described above and to provide a highly reliable method and a highly reliable system for updating a background image.
Another object of the invention is to provide a method and a system capable of rapidly updating the background image in accordance with the brightness or intensity (intensity value) change of an input image using an image memory of a small capacity.
Still another object of the invention is to provide a method and a system for updating the background image in which an intensity mismatch which may occur between the pixels updated and the pixels not updated of the reference background image has no effect on the reliability for detection of an entering object.
A further object of the invention is to provide a method and a system for detecting entering objects high in detection reliability.
In order to achieve the objects described above, according to one aspect of the invention, there is provided a reference background image updating method in which the image pickup view field is divided into a plurality of areas and the portion of the reference background corresponding to each divided area is updated.
The image pickup view field may be divided and the reference background image for each divided area may be updated after detecting an entering object. Alternatively, after dividing the image pickup view field, an entering object may be detected for each divided view field and the corresponding portion of the reference background image may be updated.
Each portion of the reference background image is updated in the case where no change indicating an entering object exists in the corresponding input image from an image pickup device.
Preferably, the image pickup view field is divided by one or a plurality of boundary lines substantially parallel to the direction of movement of an entering object.
Preferably, the image pickup view field is divided by an average movement range of an entering object during each predetermined unit time.
Preferably, the image pickup view field is divided by one or a plurality of boundary lines substantially parallel to the direction of movement of an entering object and the divided view field is subdivided by an average movement range of an entering object during each predetermined unit time.
According to an embodiment, the entering object includes an automobile, the input image includes a vehicle lane, and preferably, the image pickup view field is divided by one or a plurality of lane boundaries.
According to another embodiment, the entering object is an automobile, the input image includes a lane, and preferably, the image pickup view field is divided by an average movement range of the automobile during each predetermined unit time.
According to still another embodiment, the entering object is an automobile, the input image includes a lane, and preferably the image pickup view field is divided by one or a plurality of lane boundaries, and the divided image pickup view field is subdivided by an average movement range of the automobile during each predetermined unit time.
According to a further embodiment, the reference background image can be updated within a shorter time using the update rate of 1/4, for example, than by the add-up method generally using the lower update rate of 1/64.
According to another aspect of the invention, there is provided a reference background image updating system used for detection of entering objects in the image pickup view field based on a binarized image generated from the difference between an input image and and the reference background image of the input image, comprising a dividing unit for dividing the image pickup view field into a plurality of view areas and an update unit for updating the reference background image corresponding to each of the divided view fields independently for each of the divided view fields.
According to still another aspect of the invention, there is provided an entering object detecting system comprising an image input unit, a processing unit for processing the input image including an image memory for storing an input image from the image input unit, a program memory for storing the program for the operating the entering object detecting system and a central processing unit for activating the entering object detecting system in accordance with the program, wherein the processing unit includes an entering object detecting unit for determining the intensity difference for each pixel between the input image from the image input unit and the reference background image not including the entering object to be detected and detecting the binarized image generated from the difference value, i.e. detecting the area where the difference value is larger than a predetermined threshold as an entering object, a dividing unit for dividing the image pickup view field of the image input unit into a plurality of view field areas, an image change detecting unit for detecting the image change in each divided view field area, and a reference background image update unit for updating each portion of the reference background image corresponding to the divided view field area associated with to the portion of the input image having no image change, wherein the entering object detecting unit detects an entering object based on the updated reference background image.